Project description
Novel AI technology for dynamic and unpredictable manufacturing environments
Artificial intelligence (AI) systems are increasingly improving the automation of production in the manufacturing sector. But in order for these systems to be trusted and applicable when replacing human tasks in dynamic operation, they need to be safe and adjustable – to react to different situations, security threats, unpredictable events or specific environments. The EU-funded STAR project will rise to this challenge by designing new technologies to enable the implementation of standard-based, secure, safe, reliable and trusted human-centric AI systems in manufacturing environments. The project will aim to research and integrate leading-edge AI technologies like active learning systems, simulated reality systems, explainable AI, human-centric digital twins, advanced reinforcement learning techniques and cyber-defence mechanisms, to allow the safe deployment of sophisticated AI systems in production lines.
Objective
AI systems in industrial plants must be safe, trusted and secure, even when operating in dynamic, unstructured and unpredictable environments. STAR is a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe reliable and trusted human centric AI systems in manufacturing environments. STAR will research and make available to novel technologies that will enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, it will research technologies that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. STAR’s will research and integration leading edge AI technologies with wide applicability in manufacturing environments, including:
•Active learning systems that boost safety and accelerate the acquisition of knowledge.
•Simulated reality systems that accelerate Reinforcement Learning (RL) in human robot collaboration scenarios.
•Explainable AI (XAI) systems that boost the transparency of industrial systems and increase the trust on them.
•Human Centric digital twins enabling worker monitoring for safer and trustful production processes.
•Advanced RL techniques for optimal navigation of mobile robots and for the detection of safety zones in industrial plants.
•Cyber-defence mechanisms for sophisticated poisoning and evasion attacks against deep neural networks operating over industrial data.
These technologies will be validated in challenging scenarios in manufacturing lines in the areas of quality management, human robot collaboration and AI-based agile manufacturing. STAR will eliminate security and safety barriers against deploying sophisticated AI systems in production lines. The results will be fully integrated into existing EU-wide initiatives (EFFRA, AI4EU), as a means of enabling researchers and the European industry to deploy and leverage advanced AI solutions in production lines.
Fields of science
Keywords
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
1050 Bruxelles / Brussel
Belgium
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Participants (16)
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
1253 Luxembourg
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92230 Gennevilliers
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5656 AG Eindhoven
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062204 Bucuresti
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3100 354 Pombal
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20139 Milano
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67663 Kaiserslautern
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1000 Ljubljana
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
1210 Ljubljana
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6928 Manno
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185 33 PIRAEUS
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11632 Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
27100 Pavia
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
8500-794 Portimao
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
9712CP Groningen
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1075 AT Amsterdam
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.